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A catalog of small proteins from the global microbiome

Author

Listed:
  • Yiqian Duan

    (Fudan University)

  • Célio Dias Santos-Júnior

    (Fudan University
    Universidade Federal de São Carlos – UFSCar, São Carlos)

  • Thomas Sebastian Schmidt

    (European Molecular Biology Laboratory
    University College Cork)

  • Anthony Fullam

    (European Molecular Biology Laboratory)

  • Breno L. S. Almeida

    (Fudan University)

  • Chengkai Zhu

    (Fudan University)

  • Michael Kuhn

    (European Molecular Biology Laboratory)

  • Xing-Ming Zhao

    (Fudan University
    Zhongshan Hospital, Fudan University
    Lingang Laboratory
    Institutes of Brain Science, Fudan University)

  • Peer Bork

    (European Molecular Biology Laboratory
    Max Delbrück Centre for Molecular Medicine
    Biocenter, University of Würzburg)

  • Luis Pedro Coelho

    (Fudan University
    Queensland University of Technology, Translational Research Institute
    Queensland University of Technology)

Abstract

Small open reading frames (smORFs) shorter than 100 codons are widespread and perform essential roles in microorganisms, where they encode proteins active in several cell functions, including signal pathways, stress response, and antibacterial activities. However, the ecology, distribution and role of small proteins in the global microbiome remain unknown. Here, we construct a global microbial smORFs catalog (GMSC) derived from 63,410 publicly available metagenomes across 75 distinct habitats and 87,920 high-quality isolate genomes. GMSC contains 965 million non-redundant smORFs with comprehensive annotations. We find that archaea harbor more smORFs proportionally than bacteria. We moreover provide a tool called GMSC-mapper to identify and annotate small proteins from microbial (meta)genomes. Overall, this publicly-available resource demonstrates the immense and underexplored diversity of small proteins.

Suggested Citation

  • Yiqian Duan & Célio Dias Santos-Júnior & Thomas Sebastian Schmidt & Anthony Fullam & Breno L. S. Almeida & Chengkai Zhu & Michael Kuhn & Xing-Ming Zhao & Peer Bork & Luis Pedro Coelho, 2024. "A catalog of small proteins from the global microbiome," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51894-6
    DOI: 10.1038/s41467-024-51894-6
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    References listed on IDEAS

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    1. Martina Sassone-Corsi & Sean-Paul Nuccio & Henry Liu & Dulcemaria Hernandez & Christine T. Vu & Amy A. Takahashi & Robert A. Edwards & Manuela Raffatellu, 2016. "Microcins mediate competition among Enterobacteriaceae in the inflamed gut," Nature, Nature, vol. 540(7632), pages 280-283, December.
    2. Luis Pedro Coelho & Renato Alves & Álvaro Rodríguez Río & Pernille Neve Myers & Carlos P. Cantalapiedra & Joaquín Giner-Lamia & Thomas Sebastian Schmidt & Daniel R. Mende & Askarbek Orakov & Ivica Let, 2022. "Towards the biogeography of prokaryotic genes," Nature, Nature, vol. 601(7892), pages 252-256, January.
    3. Martin Steinegger & Johannes Söding, 2018. "Clustering huge protein sequence sets in linear time," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    4. Charles R. Harris & K. Jarrod Millman & Stéfan J. Walt & Ralf Gommers & Pauli Virtanen & David Cournapeau & Eric Wieser & Julian Taylor & Sebastian Berg & Nathaniel J. Smith & Robert Kern & Matti Picu, 2020. "Array programming with NumPy," Nature, Nature, vol. 585(7825), pages 357-362, September.
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